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Jurnal Sistem Teknik Industri
Published by Universitas Sumatera Utara
ISSN : 14115247     EISSN : 25279408     DOI : -
Core Subject : Science, Engineering,
Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering
Jurnal Sistem Teknik Industri (JSTI) of Universitas Sumatera Utara, Faculty of Engineering, Department of Industrial Engineering, was published in 1998. Until now, the number of publications has reached 21 volumes, each of which is published by TALENTA Publisher twice a year . Each volume has two publishing numbers, namely January issue numbers and July issue numbers.
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Articles 216 Documents
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The Design of a Demand Forecasting Model of Glass Bottled Tea Products With Machine Learning Approach Said Munal Akid; Ishak, Aulia; Sinulingga, Sukaria
Jurnal Sistem Teknik Industri Vol. 27 No. 2 (2025): JSTI Volume 27 Number 2 April 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i2.17069

Abstract

An accurate sales forecasting is crucial to the profits earned because it affects the company's stock management. With computational support, machine learning and artificial intelligence can continuously and automatically recognize patterns in data, thereby reducing the risk of demand unpredictability. PT XYZ is one of the companies in industrial sector that produces various beverage products. The factory in Medan. One of the products is the tea glass bottle. At PT XYZ, there are frequent differences between forecasting data and sales data, causing high error rates in production planning accuracy. This study aims to analyze the most effective model for forecasting future sales by comparing the accuracy of a Machine Learning-based forecasting model with the existing forecasting method currently employed at PT XYZ. This research was conducted using the Recurrent Neural network (RNN) method as part of the Machine Learning approach. The data that was inputted to the programme was weekly demand data, calendar day off data, temperature data, and population data. The forecasted data is weekly demand. Based on the company's historical data, a demand graph is obtained which has a cyclical pattern. From the results of forecasting using Machine Learning, an accuracy value of 99.47% is obtained with an error rate of 0.53%, which is still below the tolerance limit set by the company. The error rate shows a decrease of 14.72% compared to the error value in the previous company model. This decrease is expected to help control inventory more effectively.  
Enhancing Human Resource Performance: An Evaluation Study Using the Human Resource Scorecard Method at PT. Wanxiang Nickel Indonesia in Morowali Fole, Asrul; Safutra, Nur Ihwan; Safitri, Khoerun Nisa; Rizki Febriani
Jurnal Sistem Teknik Industri Vol. 27 No. 2 (2025): JSTI Volume 27 Number 2 April 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i2.18201

Abstract

This study evaluates the performance of human resources at PT. Wanxiang Nickel Indonesia (WNI), is influenced by a lack of responsibility, low awareness of work risks, and insufficient employee skills. The research method employed is the Human Resources Scorecard (HRS), involving a Likert scale for Key Performance Indicators (KPI) and Pairwise Comparison in the Analytical Hierarchy Process (AHP). The results of the study indicate the highest weight is found in the perspective of employees' intellectual competence (1.079) and work competence (0.981), followed by emotional competence (0.303) and personality competence (0.246). This research aims to improve human resource (HR) performance and productivity within the company. The intellectual and work perspectives play a significant role in the evaluation, while emotional and personality perspectives also contribute meaningfully. Recommendations: the company needs to develop these perspectives in a balanced manner to enhance overall human resource performance and productivity at PT. WNI.
Model for Determining the Optimum Marketing Strategy for Schneider Electric Products Using Game Theory Approach (Case Study: Authorized Distributor Schneider Electric) Ridho Habibi, Anggi; Sembiring, Meilita Tryana; Anizar, Anizar
Jurnal Sistem Teknik Industri Vol. 27 No. 2 (2025): JSTI Volume 27 Number 2 April 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i2.18363

Abstract

Market competition, sales area, and similar business process between authorized distributors of Schneider Electric Medan namely KAK and PJ have an impact on the problems experienced by consumers, resulting in sales decrease and unachieved targets by distributors. Optimal marketing strategy modeling for each distributor is needed to restore consumer confidence and also increase sales. Game theory is used to analyze the most optimum applications by finding the best mathematical model for each distributor, where each player is expected to find the most optimum indicator in maximizing profits or minimizing losses. The novelty in this study is related to the application of strategy implementation (sub-variables) which will be actions that can be taken in implementing selected strategies (main variables) for each distributor. The results of the study show that the optimum marketing strategy of the main variable for KAK is the payment strategy, and for PJ is the aftersales strategy, with the saddle point value of the game is 17.73. The applications of the optimum marketing strategy for KAK payment strategy are COD, Net OEMD, and CIA, while for PJ aftersales strategy are Warranty, Technician, and Service Center, with the saddle point value of the game is 28.18.
Increasing the Stock Taking Process Accuracy for ISO 9001 Quality Management System Fulfilment at 2W EV Manufacturer, Cikarang, West Java Maukar, Anastasia; Marcela, Anisa; Ratum, Athina Sakina
Jurnal Sistem Teknik Industri Vol. 27 No. 2 (2025): JSTI Volume 27 Number 2 April 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i2.18981

Abstract

The two-wheeled EV (2W EV) manufacturer at the centre of this study prioritizes efficiency, innovation, and adherence to ISO 9001:2015 quality requirements. However, the company encountered issues with its Supply Chain Management procedures during the ISO Surveillance 1 period, where one of the implementations was an internal audit in line with BPMS. Specifically, the results showed that the physical stock that matched the system was only 80%, which was very far from the KPI target of 95%. It hindered operations and impacted customer satisfaction. Business Process Improvement (BPI) was applied to examine the current stocking system. Comparing current processes with the best practices specified in BPMS and ISO 9001:2015 criteria was the first step in performing a thorough gap analysis. The results showed that human mistakes, machine calibration problems, a lack of standard operating procedures, inconsistent counting techniques, mixed scrap materials, and an unmanaged warehouse environment were causes of stock variations. The company made strategic changes, such as standardizing material labelling to avoid recording errors, substituting material loan for the interdepartmental purchasing system to increase accountability, and updating and enlarging SOPs to guarantee process uniformity. The business also installed an ERP system to enhance stock accuracy, facilitate real-time monitoring, and combine warehouse operations with digital tracking. As a result, by September 2024, the efficiency of stock control had increased by almost 86%. The increased stock control not only improves compliance with ISO 9001 standards, but it also increases overall operational efficiency by reducing production problems and increasing customer satisfaction.  
Quality Optimization of Fuel Transportation Tank Production Process Using Design of Experiment (DoE) at PT. Sejahtera Mandiri Pekanbaru Putra, Ahmad Mahatanzie; Anizar; Panjaitan, Nismah
Jurnal Sistem Teknik Industri Vol. 27 No. 2 (2025): JSTI Volume 27 Number 2 April 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i2.19090

Abstract

With an average error rate of 2.3%, the production of fuel transportation tanks at PT Sejahtera Mandiri Pekanbaru has defects that exceed the 2% tolerance level. Porosity, undercut, and crack are the most frequent types of defects that result in additional cost and rework time. This study aims to improve the quality of the fuel transportation tank production process at PT Sejahtera Mandiri Pekanbaru. Data shows that production errors such as porosity, undercut, and cracks have an impact on the quality of the final product. This study used a 2k full factorial design to find the main components that affect the quality of welding results. The results show that operator certification and electrode temperature oven parameters have a great influence on manufacturing defects. Maximizing the use of electrode oven at 260°C-425°C for 1 hour, electrode moisture can be eliminated and porosity can be reduced. The DoE approach is good for finding and optimizing production features to reduce defect rates. This study suggests operator training and control of process parameters to improve welding quality.
Design of Corrugated Cardboard Product Delivery Allocation Model by Considering Heterogeneous Fleet and Multi Product Zuya, Novika; Sembiring, Meilita Tryana; Nazaruddin
Jurnal Sistem Teknik Industri Vol. 27 No. 2 (2025): JSTI Volume 27 Number 2 April 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i2.19092

Abstract

Manually planning truck usage by estimating the right fleet selection, as well as considering capacity, delivery zones, and variations in demand, often results in inaccuracies. This inaccuracy has an impact on fleet utilization that is not yet optimal, characterized by low capacity used for each trip and the presence of fleets that are idle at certain times. Apart from that, inappropriate delivery allocation planning and less than optimal fleet utilization also affect delivery timeliness. This research proposes a delivery allocation model to solve the Capacitated Vehicle Routing Problem (CVRP) problem using a Genetic Algorithm (GA) implemented within the Multi-Objective Evolutionary Algorithm (MOEA) Framework. The model is designed to address CVRP by considering heterogeneous vehicle fleets, product variability, and diverse delivery destinations. The chromosome representation in the model describes the sequence of customer visits by the available fleet, while the fitness function is focused on minimizing the total traveled distance in order to maximize the efficiency of vehicle capacity utilization. Based on test results at PT In addition, this model succeeded in reducing the number of fleets used by up to 50%.
Parallel Scheduling using Genetic Algorithm and Knowledge Based Approach Gurusinga, Mentari Oktaria; Ginting, Rosnani; Sinulingga, Sukaria
Jurnal Sistem Teknik Industri Vol. 27 No. 2 (2025): JSTI Volume 27 Number 2 April 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i2.19099

Abstract

Production scheduling are very important considering the complexity of the production system. This study aims to solve parallel machine scheduling to get the best job sequence and minimize lateness. Genetic algorithm is optimization algorithms by implementing evolution process and eliminating bad solutions. Knowledge based approach (KBA) solve problems by creating a computing system to imitates human intelligent behavior. Genetic algorithm and KBA are combined with the earliest due date (EDD) rule to produce an inference engine to build more adaptive population initialization. The results of the proposed scheduling show that the rules successfully guide the search process more adaptively. The genetic operation increasing the fitness value when the job is overload or underload. When the job is underload fitness increases by 3.56%, there is no lateness and load capacity ratio (LCR) increase by 4.67%. When the overload fitness increases by 1%, lateness decreases by 4.57%, and LCR decreases by 7.56%. The increase of fitness value shows better results of the proposed job sequence with minimum lateness. The implementation of integration genetic algorithms and KBA using VB.Net language requires a reasonable computing time, which is an average of 32 seconds when running.
The Role of Human Error in Production Process Failures: A Systematic Literature Review Windy, Windy Wijayanti; Nasution, Harmein; Nurul Huda, Listiani
Jurnal Sistem Teknik Industri Vol. 27 No. 3 (2025): JSTI Volume 27 Number 3 July 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i3.18202

Abstract

Human error One of the most common causes of production failures is human mistake, which can impact product quality, operational efficiency, and workplace safety. This research aims to analyze the role of human error in the production process using various analytical methods found in the literature. This research uses a Systematic Literature Review (SLR) approach to explore the literature related to Human Error in the production process, with the aim of identifying, evaluating, and synthesizing the results of relevant studies. This research shows that 70-90% of quality defects are caused by human error, which impacts quality, increases operational costs, and poses a risk of workplace accidents. Research shows that factors such as lack of training, misunderstanding, as well as an unergonomic work environment, stress, and unclear or complicated SOPs also increase the risk of human error. The use of methods such as CREAM (Cognitive Reliability and Error Analysis Method) is employed to evaluate human reliability and predict Human Error Probability (HEP) in complex cognitive tasks. SHERPA is a method used to identify, predict, and reduce the potential for human error in a system. HEART (Human Error Assessment and Reduction Technique) is a technique designed to estimate the likelihood of human error based on specific working conditions. FMEA (Failure Modes and Effects Analysis) is a systematic method used to identify and analyze potential failures in a process or system.
Increasing Production Productivity by Improving Facility Layout Using the BLOCPLAN Method, Systematic Layout Planning, and Differential Evolution Algorithm Tarigan, Ukurta; Sembiring, Meilita Tryana; Tarigan, Indah Rizkya; Syahpturi, Khalida
Jurnal Sistem Teknik Industri Vol. 27 No. 3 (2025): JSTI Volume 27 Number 3 July 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i3.19705

Abstract

A furniture company that produces dining chairs, coffee tables, and sofa has a common problem, namely the company's inability to complete production targets within the specified time period. These general problems are the result of less efficient production paths because there is backtracking, by-passing, cross movement, and material transfer between stations that are far apart. This problem can be resolved by using improvements to the production floor layout using BLOCPLAN, Systematic Layout Planning, and Algorithms Differential Evolution. This research aims to design a production floor layout that can minimize distance, total movement moment, and material handling costs, with a line efficiency rate above 75%. The results of this research show that the proposed layout was selected using the Differential Evolution Algorithm with a displacement distance of 231.24 meters, a total displacement moment of 15,820.93 meters/month, material handling costs of IDR 1,865,920/month, and a line efficiency rate of 81.94 %.
A Quantitative Analysis of CRM Strategies on Customer Satisfaction and Loyalty: A Case Study in Space Rental Service Business Yuhelsy Gayatri Evilia; Zakaria, Muhammad; Syamsul Bahri; Meutia Fadilla
Jurnal Sistem Teknik Industri Vol. 27 No. 3 (2025): JSTI Volume 27 Number 3 July 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i3.19891

Abstract

This study investigates how Customer Relationship Management (CRM) strategies impact customer satisfaction and loyalty within the space rental service industry. Employing a quantitative approach through Structural Equation Modeling - Partial Least Squares (SEM-PLS), this study evaluates three CRM dimensions: people, process, and technology. The data were obtained via a structured questionnaire administered to 98 respondents and analyzed using the SmartPLS software. The findings reveal that process and technology significantly affect satisfaction and loyalty, whereas the people dimension has a minor impact. Specifically, the CRM process dimension positively influences satisfaction (t = 3.184, p < 0.01) and loyalty (t = 2.590, p < 0.05), while technology shows strong effects on both (satisfaction: t = 3.696; loyalty: t = 4.850; p < 0.001). The study recommends implementing operational CRM initiatives such as call centers, feedback mechanisms, and digital engagement strategies. This work contributes to the CRM literature by offering targeted insights for physical service businesses in Indonesia.

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